Cutting-stock-optimization algorithms are known in the art. Some of the better-known algorithms are those by P. Y. Wang addressing constrained one- and two-dimensional cutting-stock problems. While these algorithms tend to describe certain steps to optimize based upon certain combinatoric solutions, these solution are based primarily upon spatial considerations relating to the most optimal way to use the starting materials (e.g., a stock sheet). What is needed is an implementation of a cutting-stock algorithm that optimizes based upon not only spatial considerations and efficiencies, but also based upon scheduling, batching and labor considerations and efficiencies.